Peer-to-Peer [P2P] networks usually has the ability to perform bidirectional communication efficiently, which means both the sending and receiving end has the same transactional power and ability to communicate with one and another. In the modern world, lots of misuses occurred via network schema; now-a-days, most of the malicious activities are held via this kind of P2P data sharing mechanisms, which are held by Botmasters. The botmasters acquire the usage of P2P network and utilize it for their own purposes and make this network to act like malicious one and took the effortness of others. Lots of existing approaches are available, but all are having certain limitations, so a new botnet detection scheme is required to resolve these issues and save the network from this kind of activities, which is called "Scalable Botnet Detection Mechanism". This Scalable Botnet Detection Mechanism initiates its first activity by means of finding the connected systems into the network and make the summary of it. The next step is to manipulate the profile-handling of P2P trafficestimations as well as classify the P2P botnet traffic and legitimate P2P traffic. Simultaneously this system efficiently identifies the performance scenario of the P2P network and makes the system more scalable in further processing. The experimental results proves that our proposed approach is producing the result with more accuracy as well as more scalable than past schemes.